In this paper a comprehensive application of fuzzy set theory in structural engineering is presented. Non-stochastic uncertainty is quantified using fuzzy values. The fuzzy structural parameters are processed on the basis of a generally applicable numerical method for arbitrary linear and nonlinear fuzzy structural analyses. This method is formulated in terms of α-level optimization combined with a modified evolution strategy. The fuzzy structural responses are compared with permissible values and assessed using an analog to the Shannon entropy and defuzzification algorithms. Referring to permissible fuzzy structural responses uncertain structural design parameters are derived by applying a fuzzy cluster analysis to the fuzzy structural parameters. The nonlinear fuzzy structural analysis including uncertain structural design is demonstrated by way of an example.
Uncertainty in structural engineeringStructural engineering mainly focuses on computing structural responses, assessing structural safety, and determining parameters for structural design that meets all relevant requirements. For this purpose, the structural engineer has to apply appropriate structural models, suitably-matched computational models, and reliable structural parameters close to reality. Structural models and structural parameters have to be established on the basis of plans, drawings, measurements, observations, experiences, expert knowledge, codes, and standards. As a rule certain information regarding structural models and precise values of structural parameters do not exist. Computational models must be capable of numerically simulating the system behavior of the structural model chosen. Mathematically exact solutions, however, are only available in exceptional cases. In general, weak solutions and approximations are used, internal parameters, e.g. in material laws, have to be defined, and numerical solution techniques including lower bounds for numerical accuracy are applied. These facts show that structural engineering is significantly characterized by uncertainty. In order to perform realistic structural analysis and safety assessment this uncertainty must be appropriately taken into consideration.Different methods are available for mathematically describing and quantifying uncertainty. Some of these basic concepts are e.g. probability theory [1], including subjective probability approach [2] and Bayes methods [3], interval mathematics [4], convex modeling [5], theory of rough sets [6], fuzzy set theory [7], theory of fuzzy random variables [8], and chaos theory [9]. In the scientific literature the new uncertainty models are not only controversially discussed [10] but also increasingly implemented for the solution of practice-relevant problems [11][12][13][14][15][16][17][18]. These different developments of uncertainty models do not directly contradict each other but rather constitute an entirety.The choice of an appropriate uncertainty model for solving a particular problem depends on the characteristic of the uncertainty present in...